Gershon R, Jepson A D, Tsotsos J K
J Opt Soc Am A. 1986 Oct;3(10):1700-7. doi: 10.1364/josaa.3.001700.
The task of distinguishing material changes from shadow boundaries in chromatic images is discussed. Although there have been previous attempts at providing solutions to this problem, the assumptions that were adopted were too restrictive. Using a simple reflection model, we show that the ambient illumination cannot be assumed to have the same spectral characteristics as the incident illumination, since it may lead to the classification of shadow boundaries as material changes. In such cases, we show that it is necessary to take into account the spectral properties of the ambient illumination in order to develop a technique that is more robust and stable than previous techniques. This technique uses a biologically motivated model of color vision and, in particular, a set of chromatic-opponent and double-opponent center-surround operators. We apply this technique to simulated test patterns as well as to a chromatic image. It is shown that, given some knowledge about the strength of the ambient illumination, this method provides a better classification of shadow boundaries and material changes.
本文讨论了在彩色图像中区分物质变化与阴影边界的任务。尽管之前曾尝试解决这个问题，但所采用的假设过于严格。使用一个简单的反射模型，我们表明不能假定环境光照与入射光照具有相同的光谱特性，因为这可能导致将阴影边界分类为物质变化。在这种情况下，我们表明有必要考虑环境光照的光谱特性，以便开发一种比以前的技术更强大、更稳定的技术。该技术使用了一种受生物启发的颜色视觉模型，特别是一组颜色对立和双对立中心-周边算子。我们将此技术应用于模拟测试图案以及彩色图像。结果表明，在了解一些关于环境光照强度的知识的情况下，该方法能更好地对阴影边界和物质变化进行分类。
